Refine
Year of publication
- 2005 (2) (remove)
Document Type
- Working Paper (2)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- GARCH (2)
- Exchange Rate Mechanism (1)
- Fat-tails (1)
- GARCH-Prozess (1)
- Gauß-Funktion (1)
- Hyperbolic Distribution (1)
- Implied Probability Densities (1)
- Kurtosis (1)
- Laplace Distribution (1)
- Laplace-Verteilung (1)
Institute
While much of classical statistical analysis is based on Gaussian distributional assumptions, statistical modeling with the Laplace distribution has gained importance in many applied fields. This phenomenon is rooted in the fact that, like the Gaussian, the Laplace distribution has many attractive properties. This paper investigates two methods of combining them and their use in modeling and predicting financial risk. Based on 25 daily stock return series, the empirical results indicate that the new models offer a plausible description of the data. They are also shown to be competitive with, or superior to, use of the hyperbolic distribution, which has gained some popularity in asset-return modeling and, in fact, also nests the Gaussian and Laplace. Klassifikation: C16, C50 . March 2005.
Financial markets embed expectations of central bank policy into asset prices. This paper compares two approaches that extract a probability density of market beliefs. The first is a simulatedmoments estimator for option volatilities described in Mizrach (2002); the second is a new approach developed by Haas, Mittnik and Paolella (2004a) for fat-tailed conditionally heteroskedastic time series. In an application to the 1992-93 European Exchange Rate Mechanism crises, that both the options and the underlying exchange rates provide useful information for policy makers. JEL Klassifikation: G12, G14, F31.